This paper presents a view-independent approach to markerless human motion capture in low resolution sequences from multiple calibrated and synchronized cameras. Redundancy among cameras is exploited to generate a 3D voxelized representation of the scene and a human body model (HBM) is introduced towards analyzing these data. An annealed particle filtering scheme where every particle encodes an instance of the pose of the HBM is employed. Likelihood
between particles and input data is performed using occupancy and surface information and kinematic constrains are imposed in the propagation step towards avoiding impossible poses. Test over the
HumanEva annotated dataset yield quantitative results showing the
effectiveness of the proposed algorithm.